Tag Archives: power

The governments of G8 and G20 countries gave the OECD a global mandate to deliver country-by-country reporting, as a major tool to limit multinational corporate tax abuse, and with particular emphasis on the benefits for developing countries.

New evidence shows that – even before its implementation – the OECD standard is likely to worsen existing inequalities in the international distribution of corporate taxing rights. That is, OECD country-by-country reporting may be so skewed that it will strengthen the relative ability of its rich country members to tax multinationals, at the expense of developing countries.

The powerful potential of CBCR

‘Uncounted‘ is my shorthand for the view that who and what get counted, or not, is both a driver and a reflection of power inequalities. The failure to count marginalised groups reflects their lack of power, and also undermines the prospects for the inequalities they suffer to be addressed. The failure to count powerful groups – say, the income and assets of the top 1% – reflects the extent of their power, and also undermines the prospects of challenging the inequalities they benefit from.

The requirement for country-by-country reporting (CBCR) by multinational companies should be a paradigmatic example of transparency for accountability, where openness becomes a tool for meaningful challenge to injustice.

The Tax Justice Network has taken CBCR from the practically unheard of in 2003, when we began to develop a detailed proposal with Richard Murphy around the time of our founding, to the global policy agenda when in 2013 it formed an important part of the workplan for both the G8 and G20 (see film at 2 min 50 in particular).

The case for CBCR is that it provides additional, public information on the location of the activities of multinational companies, in order to improve accountability in a range of ways.

First among these is tax. Multinationals can be held to account against the global aim of improving the alignment between where their economic activity takes place, and where taxable profit is declared.

Openness of CBCR to tax authorities allows measures of misalignment to be easily calculated, in order to identify the major tax risks. Openness of CBCR to the public allows media and civil society activists to hold tax authorities to account; and allows investors and market analysts to identify share prices risks and so price multinationals more efficiently.

In this way, public CBCR is a transparency measure that genuinely shifts power, and drives greater accountability in multiple channels.

The disappointments of OECD CBCR

Sadly, the OECD approach demonstrates just how the undermining of a transparency measure can exacerbate inequalities and weaken accountability.

First, the power of lobbying saw the idea of public reporting knocked on the head – so at least in the OECD standard, there’s no commitment to allow investors, analysts, journalists or activists the opportunity to hold multinationals accountable.

Second, things went even further into reverse when the OECD agreed – almost unbelievably – not to support individual tax authorities asking for CBCR from multinationals operating in their jurisdiction.

Think about that for a moment: so successful has been the lobbying against potential accountability, that something tax authorities could have done unilaterally before the OECD got the CBCR mandate, would now be seen as counter to the international standards.

Instead, tax authorities of host countries are expected to apply for the information to be provided by the tax authority of the home country – if the latter has it, if there is an information exchange protocol in place, if the host country has committed to confidentiality (no way back into public openness here).

New evidence

And now accounting firm EY has published the results of a survey on implementation of CBCR. The new evidence appears to confirm strongly the fear that each watering down of CBCR at the OECD will be to the detriment not only of openness and accountability, but also to the taxing rights of non-OECD members.

The full report (pdf) is well worth reading. Most striking visually (and a big tip of the hat to Christian Hallum at Eurodad for this) are the two maps that summarise key findings.

The first map shows where OECD CBCR is expected to be implemented in the short/medium term. As you might expect, given the global distributions of tax authority capacity and of multinational company headquarters, implementation is expected in almost all OECD members (see figure also); and in barely any non-OECD members.

The second map shows the jurisdictions which will be able to take part in CBCR information exchange – that is:

Signatories of the multilateral competent authority agreement for automatic exchange of information based on Article 6 of the Multilateral Convention on Mutual Administrative Assistance in Tax Matters (as of 1 August 2015), as well as other countries expected to participate in the automatic exchange of CbC report information based on the results of our survey (“additional jurisdictions”); and

Countries that underwent the “peer reviews” of the Global Forum on Transparency and Exchange of Information for Tax Purposes (as of 1 August 2015) and were found to be “compliant,” “largely compliant” or “partially compliant” with the confidentiality standard.

While there are interesting variations, and some developing countries do stand to benefit, the overall picture is a depressing one.

The most recent IMF research suggests that the impact of multinational avoidance on revenues is around three times as high for developing countries (the authors provide an ‘illustrative calculation’ of 1.7% of GDP) as it is for OECD members (0.57%).

In general, the approach to CBCR will ensure better information on multinational tax risk for the richer countries, mainly OECD members. Now in this case, there can be no doubt that information is power.

As a result, the major inequality in the distribution of taxing rights between countries rich and poor is likely to be exacerbated by OECD country-by-country reporting.

Where do we go from here?

Consider two more positive points. First, the widespread adoption of OECD CBCR among jurisdictions where most multinationals are headquartered means that questions of compliance cost should be behind us.

Where, we may now ask, are the transparency champions? Which multinationals will step forward, and lead their counterparts by making public their data? With carrots like the Fair Tax Mark available… Watch this space.

And second, there are active processes in a range of jurisdictions including the EU, to determine whether to make their CBCR fullly public.

Given the failure of OECD CBCR to level the playing field – in fact quite the reverse – the only way to meet the G8 and G20 commitment to developing countries is for them to require public CBCR.

Once again, transparency champions will be required to lead the way. Facing an opposition newly seized of the tax justice agenda, might the UK government follow through on its 2013 leadership?

June 2015. Surprising everyone by actually arriving within the stated month, here’s the sixth Tax Justice Research Bulletin – a monthly series dedicated to tracking the latest developments in policy-relevant research on national and international tax, available in full over at TJN.

This issue looks at a new paper in The Lancet on the potential links between direct taxation and health outcomes including child mortality; and at research on the suitability or otherwise of accounting data for tax purposes. The Spotlight falls on tobacco taxes, the shameful manipulation of economic arguments by Big Tobacco, and a paper entitled The Single Best Health Policy in the World: Tobacco Taxes. If this issue was any more health-y, you could put a vest on it and send it out to do a half-Iron Man with Owen Barder.

This year’s thematic focus was on the flawed notion of “competition” between nation states, and there’s a cracking set of papers from a whole range of disciplines (from philosophy to accounting) and backgrounds (including practitioners, civil society researchers and academics from universities from Hong Kong to Barcelona); and touching on all sorts of tax and non-tax aspects of ‘competition’, with insights into everything from Guernsey’s dominant investment position in annexed Crimea, to the ‘voluntariness’ of migration; and from regulatory responses of commodity traders to the role of KPMG in systemic regulatory arbitrage.

The workshop ended with a really engaged discussion about the relative merits of taking on the entire logic of state competition, versus the practical value of keeping focus on tax.

There’s certainly an important challenge in reclaiming the word ‘competition’ in this context, which has been used almost as a synonym for ‘no government intervention’ – when ensuring competition may well require greater intervention, in order to prevent power abuses leading to further concentration. The creators of the ‘Global Competitiveness Index’, for example, probably don’t see themselves as advocates for a world regulatory body, preventing unfair competition between states…

Submissions for the Bulletin, including tax-related melodic suggestions, are most welcome.

What we measure affects what we do; and if our measurements are flawed, decisions may be distorted…. [I]f metrics of performance are flawed, so too may be inferences we draw.

The UN Secretary General was told two years ago by the 2012–13 High Level Panel of Eminent Persons on the Post-2015 Development Agenda that any follow-up to the Millennium Development Goals (MDGs) had to include adata revolution.

In common with the UN global thematic consultation on inequality earlier in 2013, the High Level Panel recognised that challenging inequalities and better data collection are inextricably linked – because better data make it clear which goals are and are not being met, and because with better data we can all demand answers and action.

So the data revolution can only be about changing the balance of power. Yet much of the current discussion emphasises purely technical reforms instead.

I use the term ‘Uncounted’ to describe a politically motivated failure to count that reflects power. It ignores people and groups at the bottom of distributions whose ‘uncounting’ adds another level to their marginalisation. It ignores people at the top whose uncounting hands them even greater power.

Why do we fail to count well at the bottom? This figure shows three different series for primary school enrolment in Kenya. One comes from the Kenyan National Bureau of Statistics (KNBS); one from the Demographic and Household Surveys (DHS); and one from the Ministry of Education (MOE). MOE data come directly from schools and are used as the basis for funding decisions.

Now, MOE trends tell you that progress is rapid and unsustained, while surveys look static. Which do you believe? If your children are in Kenyan state education, how well counted do you feel?

Not that survey data are perfect either. Six groups are systematically excluded from most household survey and census returns. Excluded by design are the homeless, those in institutions and nomadic populations. Ignored by undersampling are those living in fragile, disjointed households, in areas facing security risks and in informal settlements. These groups, thought to amount to around 250 million uncounted people – roughly 3.5% of today’s global population – obviously contain a disproportionate share of the world’s poorest people. They are being systematically failed even in the ‘best’ counting approaches we have.

It’s no coincidence that people in poverty are excluded. Nor is it because of technical problems that Sudan’s government in Khartoum suppresses publication of data on regional development outcomes. Or that the deaths of those living with disabilities in the UK go uncounted.

As for counting at the top, it’s equally no coincidence that high-income households are undersampled in surveys. Or that even when tax data are used to adjust the picture, major wealth – $8 trillion? $32 trillion? – remains uncounted. Or that the OECD, charged with measuring the ‘misalignment’globally between the profits of multinational companies and the actual location of their economic activity, has so far been unable to lay its hands on the necessary data.

Our choice of measure is also important – and also political. Take a look at this chart which shows how two measures, the Gini coefficient and the Palma ratio, come up with radically different answers to the same question about income distribution. Has UK wealth inequality been flat across the crisis? Or did it fall sharply, then immediately rebound even more dramatically?

The Gini coefficient embodies such strong normative views (pp. 129–144) that it doesn’t capture well changes in the top 10%, or in the bottom 40% where most poverty lies. It is very encouraging (to me!) that instead the Palma ratio has featured in recent drafts of the post-2015 indicators.

The Palma – which expresses the ratio of income shares of the top 10% to the bottom 40% – also embodies a normative view, but it’s absolutely explicit about it. The chart of UK wealth distribution across the financial crisis shows why the Gini gave rise to so many congratulatory headlines about stable inequality, and why they’re wrong.

What might an actual ‘data revolution’ look like? If there’s no recognition of the political nature of the problem, then we’d be fooling ourselves to expect any great change: the same people and the same things will continue to go uncounted.

What’s noticeable in the discussion so far is that there has been a great deal more attention paid to the uncounted at the bottom than at the top. There’s been precious little mention of Piketty’s proposal for a global wealth register, for instance, or of specific measures that would eliminate anonymous company ownership, require states to exchange tax information with each other (think SwissLeaks), or multinational companies to publish country-by-country reporting (think LuxLeaks). Yet if we don’t start counting things that make elites uncomfortable, then we’re not doing it right.

[A long post, building to an Uncounted proposal on UK inequalities monitoring and data.]

Last week’s UK election produced a majority for the centre-right Conservatives – a majority of parliamentary seats, that is, albeit with 36.9% of votes.

Framing a victory

The winning framing seems to have been one of Conservative economic competence, set against two claimed threats from change:

a ‘coalition of chaos’ featuring Labour and the Scottish National Party (despite the 2010-2015 Conservative-Liberal Democrat coalition having set something of a modern precedent in UK politics, and both Labour and the SNP having explicitly ruled out a coalition); and

a return to Labour’s crisis-inducing economic incompetence (despite a fairly broad expert and academic consensus that Labour’s economic policy before and through the crisis was pretty reasonable; and that the the 2010 coalition’s austerity measures, largely abandoned in 2012, were a triumph of ideology over economic commonsense, with predictable macroeconomic and human costs).

Much has been written, and much more will be, on the reasons for the framing success – including the breadth of media support for a Conservative victory, and not unrelated, the ‘mediamacro myths‘ per Simon Wren-Lewis that ensured popular perceptions of economic (mis)management remained far adrift of expert analyses.

Lost in construction?

The campaign featured more heat than light on the impacts of austerity, and the related inequalities. Everyone said they’d reduce tax avoidance, some said they’d reduce tax evasion, but there was barely a specific policy proposal among the lot.

Nobody mentioned that the 2010 UK government had been the only major economy to cut tax during austerity – so that spending cuts were, uniquely, greater than the deficit reduction that was achieved.

Marginalisation in (as?) policy design

Jim Coe has written a typically thought-provoking piece on the challenges facing broadly progressive activists in the UK now.

Jim looks at a model of four groups in terms of (i) their respective power and (ii) the extent to which they are ‘socially constructed’ as deserving policy support or not:

Advantaged groups – such as small businesses, or homeowners – are treated with respect and perfectly placed to receive policy benefits.

Contender groups – such as some in big business (bankers etc) – are not seen so positively. But, because they are powerful, they can gain hidden benefits whilst resisting attempts to impose policy sanctions.

Dependents – groups who require some kind of support, students, workers on low pay – are seen generally positively but lack political power. They may be viewed as ‘good people’ but the support offered will often be inadequate, and they lack the influence to make enhanced claims.

‘Deviants’ both lack power and are negatively perceived. The list of groups who fall in this category seems to be ever-growing. Criminals, drug users, and, increasingly, many migrant groups, and families in poverty, etc. etc. Few speak on their behalf and policy makers are reluctant to be seen providing ‘good things to bad people’.

Jim’s post is well worth reading, as he builds from here to discuss the ways in which positions can be self-reinforcing over time, and what the strategies may improve the prospects for reversal or resistance in particular aspects. I want to make a comment and a proposal.

Austerity and uncounting

There is presumably always pressure, in the model above, to squeeze those in the low power group deemed deserving of policy support, into the undeserving group: in the model’s terminology, to see dependents increasingly as deviants.

In the context of a commitment to austerity – whether economically sensible or not – there is a specific need to reduce the total of policy support, potentially giving rise to a political climate which sets those with power (more) strongly against those without.

In the UK the growth in abuse directed at people living with disabilities, including learning disabilities, is a particularly damning feature of this trend – along with the disproportionate cuts in benefits applied. The rise of explicitly anti-immigrant positions across the major political parties is another.

A flipside of this that one might expect to see is a (quiet) reduction in the fiscal contribution of those with power – perhaps explaining the UK’s real reduction in tax revenues, though not necessarily why the UK is an international outlier in this regard.

The incoming government has committed to sharper cuts than it managed in the previous parliament: with a similar revenue trajectory, the risk is of a significant worsening in inequalities, and the weakening more generally of the state’s capacity to deliver support to ‘dependent’ groups.

Finally, Jim’s model provides one more way of thinking about the phenomenon of Uncounted (the importance of power for being counted, and vice versa).

This last parliament has seen some fairly striking uncounting – none more so than the decision to stop collecting statistics on the deaths of those receiving certain benefits, but the continuing failure to implement fully the government’s own review recommendations about statistics on lives and deaths of people living with learning disabilities should not be overlooked either.

Failing to count bad group outcomes represents a substantial worsening of the inequalities faced – but often a politically beneficial one for governments.

A modest proposal

Without getting into party political issues of leadership direction, are there reasonable measures that would support greater accountability to limit damaging inequalities in the current parliament, and promote greater attention to these issues in future political debate?

The one that springs to mind is simply to track the data – its existence or otherwise, and its values where it does exist – on each of the major inequalities in the UK.

The high-level group that David Cameron co-chaired on the post-2015 successor to the Millennium Development Goals was absolutely clear on the importance of disaggregated data to ensure that all groups and people benefit:

The suggested targets are bold, yet practical. Like the MDGs, they would not be binding, but should be monitored closely. The indicators that track them should be disaggregated to ensure no one is left behind and targets should only be considered ‘achieved’ if they are met for all relevant income and social groups. We recommend that any new goals should be accompanied by an independent and rigorous monitoring system, with regular opportunities to report on progress and shortcomings at a high political level. We also call for a data revolution for sustainable development, with a new international initiative to improve the quality of statistics and information available to citizens.

A baseline of available UK data on a full range of aspects of human development, fully disaggregated as Cameron’s panel demanded, showing levels of inequalities and also gaps in data, as at 7 May 2015; and

A tracking and ongoing analysis of changes in that data and its availability over the course of the current parliament (and ideally beyond).

Naturally, this would be a fully open data pie in the sky, and ideally one or more groups like Open Knowledge Foundation would play a role too.

Here are four big bullets from ActionAid UK’s new report, ‘Close the gap!’:

Women earn 15% less than men on average. If women’s wage were raised to the level of men’s wages in all developing countries, with all else held equal, women would earn $2 trillion more.

Women’s participation is 37% lower than men’s. Raising women’s participation to equal that of men, all else held equal, would see women earn $6 trillion more.

Addressing both the wage gap and participation gap simultaneously in this way would see women earn $9 trillion more.

Extending the analysis to rich countries generates a global total gap of nearly $17 trillion.

Congratulations are due – it’s an enormously important issue and these are striking findings, so I hope it gets serious attention. [Disclosure: I commented on an early draft of the quantitative analysis.]

How good are the numbers? (Uncounting ahoy)

The methodology is fairly straightforward, and clearly set out in the report. If there’s a weakness, and there is, it’s in the data. ActionAid are commendably straightforward about this too:

Pay gaps and ratio of male to average wage taken from ILO data. There are many missing values. We fill the pay gaps using regional medians…

Inevitably given the extent of missing values, some of the extrapolations of pay gaps verge on the heroic. I’d judge the methodology to be reasonable in the data context, but make no mistake – the data context is shocking. Meanwhile,

I’ve no reason at all to doubt the quality of these data, but how can it be that there is no better source than these multi-year averages calculated by a single IDPM researcher a couple of years ago? The report quite rightly highlights the gender implications of the failure to count unpaid work, and to this can be added the pretty desperate state of counting of paid work.

Normally I would insert some blather here about post-2015 and reasons to be cheerful, but ba’ hairs I’m having a bad day. Talk to me about the data revolution when you’ve decided who’ll be first up against the wall. It seems we’re really talking about incremental data reforms. Either way, serious improvements in gender disaggregation are urgently needed.

Some progress will certainly come via the Sustainable Development Goals, but let’s not kid ourselves. The Open Working Group SDG proposal includes:

8.5 by 2030 achieve full and productive employment and decent work for all women and men, including for young people and persons with disabilities, and equal pay for work of equal value

That should do it, right? Maybe. Remember the current failure of counting is the end-product of 15 years of the Millennium Development Goals – which included this more prominent target:

Target 1.B: Achieve full and productive employment and decent work for all, including women and young people

Still, I suppose the MDGs didn’t include a data revolution so this time is bound to be different. Right?

Three points of caution

Presentation. One issue to mention is the possibility that the number take a life of its own, as these numbers can, and ends up being presented as the cost of sex discrimination in employment. It’s not this – because there’s no reason to think that $17 trillion of extra employment will suddenly come into being if the world was fairer, so a good part of this would likely come instead from reduced male employment earnings. The $17 trillion reflects the estimated scale, in currency terms, of the sex gap in employment in developing countries.

Economics above the rest? While it makes sense in advocacy terms to go for a big number (that may be why you’re reading this post, for example), it’s unfortunate if it adds to the sense that only economic arguments matter. As the report makes clear elsewhere (in the bits that won’t make any headlines), the deeper dignity and empowerment dimensions are much more important and complex.

Inequality reinforced? A related point is that the nature of the calculation reinforces a different aspect of inequality. Consider two economies of the same size with the same gender participation gap but where the average wage in one is twice as big as in the other. The methodology will value the gap in the first as also being twice as big as the other. Now that seems unhelpful, on the face of it, if we would broadly think that the two economies and their respective gaps are of equal importance. In fact, we might think that the gap in the lower-income country is more important, since it is more likely to imply poverty for those on the wrong end.

To give a sense of how important this potential problem is within the overall calculation, compare the developing country and advanced country totals. In particular, note that the wage gap in rich countries is nearly twice that in developing countries. We certainly shouldn’t downplay the sale of the problem in rich countries, and I’m glad ActionAid have made the analysis global rather than giving the impression it’s only a developing world problem. But at the same time, measuring in dollar terms may overstate the relative importance of the problem in high-income settings; when the human costs in lower-income contexts may be equal or greater.

Imagine a world of such structural inequality that even the questions of who and what get counted are decided by power.

A world in which the ‘unpeople’ at the bottom go uncounted, and so too does the ‘unmoney’ of those at the very top. Where the unpeople are denied a political voice. Public services. Opportunities. And the unmoney escapes taxation, regulation and criminal investigation, allowing corruption and inequality to flourish out of sight.

We may pride ourselves on being the generation of open data, of big data, of transparency and accountability, but the truth is less palatable. We are the generation of the uncounted – and we barely know it.

Counting is fundamentally political. Decisions about what and who to count not only reflect unequal power, they are also a major driver of inequalities. Our failure to acknowledge and challenge these automatic tendencies means that we unthinkingly facilitate them.

There are two major elements to the uncounted: that which is uncounted because of a lack of power, and that which is uncounted because of an excess of power. In addition, the category of that which is only counted in private has its own power dynamics. Policy implications vary according to the context and the type of uncounted – but there are some very clear channels if we decide – as we surely must – to address the problem head-on.

This site will include semi-regular blogging (that may eventually result in a book) on these issues and others, along with related publications and data as they appear. There’s also a particular space for the Palma: a measure of inequality, developed with Andy Sumner on the basis of Gabriel Palma‘s analysis of the income distribution.